Two GTX 580s in SLI are responsible for the AI we have today — Nvidia’s Huang revealed that the invention of deep learning began with two flagship Fermi GPUs in

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Two GTX 580s in SLI are responsible for the AI we have today — Nvidia's Huang revealed that the invention of deep learning began with two flagship Fermi GPUs in

Nvidia and OpenAI forge $100 billion alliance to deliver 10 gigawatts of Nvidia hardware for AI datacenters

Jensen Huang revealed that the AlexNet developers built their image recognition algorithm on a pair of GTX 580s in SLI. Furthermore, the network was optimized to run on both GPUs, and the two GPUs exchanged data only when needed, significantly reducing training time. This makes the GTX 580 the world's first graphics card to run a deep learning/machine learning AI network.

Ironically, this milestone was made at a time when Nvidia had very little investment in AI. Most of its graphics research and development was geared toward 3D graphics and gaming, as well as CUDA. The GTX 580 was designed specifically for gaming and had no advanced support for accelerating deep learning networks. It turned out that GPUs' inherent parallelism was exactly what neural networks needed to run fast.

Jensen Huang further revealed that AlexNet, combined with its use on the GTX 580s, is how Nvidia got into developing AI hardware. Huang stated that once the company realized deep learning could be used to solve the world's problems, it invested all its money, development, and research in deep learning technology in 2012. It is what gave birth to the original Nvidia DGX in 2016 , which was shipped to Elon Musk, the Volta architecture with first-gen Tensor cores , and DLSS . If it were not for a pair of GTX 580s running AlexNet, Nvidia might not be the AI giant it is today.

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  1. Two GTX 580s in SLI are responsible for the AI we have today — Nvidia’s Huang revealed that the invention of deep learning began with two flagship Fermi GPUs in
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